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Enterprise resource planning (ERP) systems that are equipped with numerous features and functionalities help to improve the profitability of construction corporations around the world through enhancing the efficiency of the functions related to cost management. Thus, the purpose of this study was to investigate the applicability of ERP systems for cost management of building construction projects in Sri Lanka.

A qualitative technique was used in this study, which comprised two-round Delphi-based semistructured interviews. Purposive sampling was used to determine the interviewees. Content analysis was used to evaluate the collected data.

The findings of this study identified the ERP system as a strategic tool for gaining a competitive advantage for an organization while confirming 14 uses of ERP systems and 16 stages of the cost management process. Eighteen issues were finalized at the end of the interview rounds while categorizing the suitable ERP applications at each stage of the cost management process.

Even though there are numerous distinct studies conducted on cost management and ERP systems, there has been a lack of studies conducted on the synergy between these two areas that can be adapted for the building projects in the Sri Lankan context. Therefore, the findings of this study can bring a new paradigm to the Sri Lankan construction sector by influencing the adaption of correct ERP systems at numerous project stages by providing a competitive edge.

The objective of this comparative quantitative study is to examine hypotheses regarding the impact of asset management and intellectual capital (IC) on the financial performance of the construction sector in the ASEAN-5 throughout 2019–2022 with enterprise resource planning (ERP) as a mediator variable.

A final sample of 65 construction industries listed on stock exchanges during 2019 and 2022 in ASEAN-5 (Indonesia, Philippines, Malaysia, Thailand and Singapore) was selected using the purposive sampling method. This research employs market-to-book value (MBV) as a measure of IC. The study also used path analysis, the Sobel test and analysis of variance test (ANOVA).

The findings demonstrate that asset management, intellectual capital and ERP have a significant and favorable impact on return on asset (ROA). Additionally, the asset management and IC of the ERP display weak and substantial outcomes. The implementation of ERP was also shown not to operate as a mediating factor. The ANOVA results on financial performance indicate significant differences for the year 2019. Furthermore, the use of various ERP software types demonstrates a comparable impact on enhancing financial performance.

This is the first study that utilizes ERP to mediate management asset and IC on financial performance. The ASEAN-5 construction sector is representative of developing nations' economic condition, offering the possibility to avoid the global economic collapse in 2023 and recover despite economic volatility.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making.

The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency.

The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests.

The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs.

The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making.

The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem.

This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

The primary objective of this research is to identify and analyze the influence of digital marketing practises on performance of business of manufacturing enterprises in Delhi-NCR. A quantitative and descriptive research design was implemented in this study. 368 participants from various enterprises were chosen. Questionnaires were used to collect data on the benefits and challenges which are perceived of digital marketing, as well as usage and business performance of these enterprises. SPSS v24.0 is utilized to carry out statistical analysis on the collected data. The study discovered that advantages and problems of digital marketing practices influenced the usage of digital marketing. Furthermore, the execution of digital marketing had a prominent influence on sales and total number of customers of these enterprises, and this relationship was moderated by type and size of businesses. It was discovered that using digital marketing strategies increased business profits by raising digital marketing awareness among consumers and various industries. It made digital marketing easier to implement in various businesses. However, research should be conducted for appropriate generalization in a larger scale.

This study looked at the potential applications of geographic information systems (GIS) and remote sensing (RS) for inclusive community development and participation, sustainable tourism, and rural community-based natural resource management (CBNRM) in sub-Saharan Africa and other rural areas worldwide.

To evaluate resource management systems for rural tourism and the environment in Africa and abroad. The study makes use of reviews of relevant literature and documents, and while linking applications for sustainable tourism and local community empowerment with CBNRM and GIS, vital content was manually analyzed.

The study shows a potential affinity between agricultural and tourism businesses that GIS in line with the CBNRM conception can strengthen. In many rural and underdeveloped regions of the continent, this highlights the need for a credible and varied tourism strategy to develop and empower the relevant communities.

Most agricultural communities in Africa are located in low-income regions. Such areas are rich in natural wildlife and have popular tourist destinations. A mix of regional community development initiatives can be built using GIS, sustainable tourism, CBNRM, and community-based tourism (CBT).

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

This study aims to examine the application of Wardley mapping on developing and implementing an information technology (IT) strategy in a small-scale business. This case study illustrates the potency of multitier analysis using Wardley mapping technique to explore capability gaps and areas to focus on before undertaking IT projects.

This study uses a single case of enterprise resource planning implementation and subsequent abandonment in a small-scale manufacturing company.

This study demonstrates that multitier analysis using Wardley mapping enables a comprehensive examination of organizational capabilities, including a granular analysis of issues that must be managed for successful implementation of an IT project.

While the findings of a single case study offer limited generalizability, this study sets out the approach that can be extended in more complex settings.

The approach to understanding the organizational capabilities required to execute IT projects, or any change management project, offers significant benefits to managers and leaders.

The authors make two distinct contributions: The Wardley mapping technique has emerged as a new tool for understanding business models, particularly in government projects notable in the UK. This study extends its application to the small-scale manufacturing sector. The second contribution is elaborating on multitier analysis, which allows a granular analysis of issues that can impair the IT project implementation, including an assessment of the organizational capabilities required to deliver a successful project.

The aim of the study is to investigate the factors that influence the adoption of e-procurement by businesses in the specific context of Saudi Arabia.

This study uses the firm-level data of World Bank Enterprise Surveys 2022 of Saudi Arabia covering 1,573 enterprises. The association between firm characteristics and the adoption of e-procurement by enterprises has been examined through the chi-square test. Further, a logistic regression model has been fitted to estimate the factors affecting adoption of e-procurement.

About 10 % of the enterprises reported that they adopted e-procurement as the establishment’s main technology to manage procurement and supplier chain by enterprises. A statistically significant association has been found between e-procurement vis-a-vis firm characteristics. Moreover, logistic regression analysis indicated that large and innovative enterprises, with digital presence in terms of website, holding a bank account and access to credit are more likely to adopt e-procurement.

This study offers valuable insights into the factors that influence the adoption of e-procurement by businesses, which helps the supply chain manager to develop and operationalize the digital supply chain through e-procurement in the context of Saudi Arabia.

This paper can provide significant insights for promoters and supply chain managers in Saudi Arabia, who are now focusing on the digital transformation of businesses. By understanding the factors affecting e-procurement by firms, they can smooth the supply chain.

Small and medium enterprises (SMEs) significantly contribute to economic growth, development, exports and employment of the nations. To maintain competitiveness in today's market, SMEs must explore and identify enablers to enhance their digital transformation process. This paper aims to shed light on some essential enablers SMEs can use to implement digital resilience successfully.

The quantitative assessment and validation of the enablers have been done using powerful and novel techniques, namely, the Delphi method, “fuzzy interpretive structural modelling” (F-ISM) method and “cross-impact matrix multiplication applied to classification (MICMAC)” analysis. The F-ISM model is developed using the information drawn from digital transformation experts and practitioners involved in the digital transformation process for SMEs. Furthermore, the F-ISM model provides four paths to complete the pathway to digital resilience.

The F-ISM and MICMAC analysis revealed four ways to enhance the digital transformation process in SMEs. These enterprises can utilise these path assessments to become digitally resilient in the present dynamic scenario. To enhance digital resilience among SMEs, the study identified ten enablers. Among these, “management competencies” was the most crucial, followed by “knowledge management” and “monitoring and controlling”.

The present study is limited in that the data used to develop the models were collected from a small group of industry experts whose opinions may not exhibit the comprehensive views of the population.

The findings can help SMEs enhance the digital transformation process by taking up different pathways to integrate the various enablers of digital resilience depending on resource availability.

The results indicate the most critical and influential enablers for enhancing digital resilience among SMEs. This research can be valuable to academicians, industry practitioners and researchers for guiding their future work.